Enables satellite imagery analysis through Google Earth Engine, allowing users to search datasets, calculate vegetation indices like NDVI, filter collections by location and date, and export imagery to cloud storage. Supports major satellite datasets including Sentinel-2, Landsat, and MODIS for applications like agriculture monitoring and deforestation tracking.
Production-ready satellite imagery analysis server that enables natural language queries for Earth observation data, including land cover classification, vegetation monitoring, water detection, change detection, and automated environmental reporting.
Computes soil resource concern ratings for an area of interest using USDA Soil Data Access and exposes them as MCP tools, resources, and prompts for AI-assisted conservation planning.
Provides tools to search, download, and manage satellite imagery from all Copernicus Sentinel missions via the Copernicus Data Space ecosystem. It enables advanced geospatial queries, temporal coverage analysis, and automated data management for Earth observation tasks.
Enables search and retrieval of calibrated SWAT+ watershed models, national groundwater lithology and PFAS inventories, plus API-key-secured ordering and downloading of custom watershed models.
MCP server for interacting with Google Earth Engine, enabling geospatial analysis such as dataset visualization, statistics computation, and search via AI assistants.
